O pozici
We help the world run better
At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging – but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.
Co budeš dělat
- As a Expert Machine Learning Engineer your is to design, develop, and optimize innovative machine learning systems and systems based on product requirements. By staying updated on machine learning operations and engineering best practices, the role drives the integration of machine learning models into production software solutions, supporting real-world applications.
- You'll set the technical direction for production-grade AI products — agentic systems, LLM-powered applications, and semantic retrieval pipelines on a modern cloud platform — that put state-of-the-art capabilities into the hands of SAP customers and measurably improve how they run their business.
- You'll architect agentic workflows and orchestration patterns that automate complex, multi-step business processes across the enterprise, turning what used to be manual effort into reliable, scalable outcomes — and establishing the reusable building blocks other teams build on top of.
- You'll take AI from prototype to enterprise scale , setting the MLOps and AI quality-assurance standards — evaluation harnesses, CI/CD, monitoring, guardrails, model versioning, and cost/latency discipline — that other teams adopt across the area.
- You'll raise the bar on AI output quality, trust, and governance by engineering the context, prompts, retrieval, and evaluation that make our models accurate, safe, and compliant — and by treating data ethics, privacy, and responsible AI as first-class architectural concerns.
- You'll work with AI as a daily craft — using AI-assisted development and agentic tooling to multiply your own and your teams' output, while shaping how the broader engineering organization adopts these practices.
- You'll shape multi-quarter strategy and what's next by partnering across Engineering, Product, Design, and business stakeholders to identify where AI creates the biggest leverage, mentoring senior engineers and architects, and turning ambiguous problems into clear, executable roadmaps that advance SAP's applied AI portfolio.
Koho hledáme
- Expert level of software engineering and architectural depth — you've designed and shipped large-scale, mission-critical SaaS on modern cloud platforms, with the judgment that comes from seeing multiple generations of technology mature in production.
- A modern, hands-on perspective on AI and machine learning — strong working knowledge of deep learning, LLMs, agentic systems, semantic retrieval, and context engineering — and you use AI tooling as a daily part of how you design, build, and ship software.
- Mastery of engineering craft applied to AI — fluency in Python/Java and the ML ecosystem (e.g., PyTorch, Hugging Face), comfort handling large-scale, real-world data , and a track record of turning prototypes into production-grade services with clean APIs, observability, evaluation, and CI/CD.
- A proven record of scaling AI systems in production — you've set the MLOps and AI quality-assurance standards (evaluation harnesses, monitoring, versioning, guardrails, cost and latency discipline) that other teams adopt, and you make the trade-offs that determine whether AI products succeed at enterprise scale.
- Cross-organizational technical leadership — you partner naturally with Product, Design, and business stakeholders, mentor senior engineers and architects, and turn ambiguous, multi-quarter problems into clear roadmaps that teams execute against.
- A principled view on responsible AI — you treat data ethics, privacy, and AI governance as first-class architectural concerns, and leadership relies on you to weigh in on the hard trade-offs between capability, risk, and customer impact.
- Transferable strengths that compound here — distributed systems, large-scale SaaS, and architecture leadership translate directly into building reliable, secure, operationally sound AI products. What sets you apart is the breadth of experience plus a genuine adoption mindset toward the AI frontier .
Benefity
- What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.
